Free Navigation at arculus: Precise, Tagless Localisation
August 26, 2025
The arculees, our Autonomous Mobile Robots, must navigate through their environment to ensure smooth intralogistics operations. While they previously relied on physical markers at client sites, that’s no longer necessary. With the development of our Free Navigation technology, the arculees can now localise and move freely, i.e., without any pre-installed markers. Let’s hear from Dennis Schradick, our Robotics Software Engineer, on how this advanced technology works, reducing costs while improving efficiency.
Autonomous Mobile Robots (AMRs) like our arculees navigate through an environment to efficiently perform their designated tasks, such as material transportation in warehouses. Previously, the arculees relied on physical floor landmarks such as QR code markers to find their way at a site. While these markers enabled millimetre-level localisation accuracy, they required time- and cost-intensive pre-installation, calibration, and maintenance. To make the navigation process thus smoother and marker-independent, arculus adopted the technology called free navigation. Dennis Schradick, our Robotic Software Engineer, elaborates,
"Free navigation is what we call it at arculus. It is the technology that allows our arculee to localise itself and therefore navigate around in any environment without the need to alter the site physically. With free navigation, we are only relying on what's already there, both in terms of the operating environment and the sensor setup of the arculee."
Dennis working with arculees in the testing area of our Munich office
How does Free Navigation Work?
At its core, free navigation enables the arculees to understand where they are in an environment and move autonomously. Dennis explains how it works through a combination of sensing and localisation techniques:
1. Sensing
For a robot to move autonomously, it first needs to perceive its own motion and its surroundings. The arculee achieves this through two types of sensors: Relative Sensors & Absolute Sensors
a. Relative Sensors
Relative sensors provide estimates of how the robot has moved based on its own internal measurements. These include:
Wheel speed sensors: measure how fast the wheels are turning.
Inertial Measurement Unit (IMU): measures acceleration and rotational velocity.
By mathematically integrating these measurements, the system can estimate how far the robot has travelled and how much it has rotated. This data gives an estimate of the robot’s current position and orientation relative to the initial point of operation. However, relative sensors are subject to drift over time due to issues like sensor noise and wheel slip, which can cause the estimates to become less accurate over time.
b. Absolute Sensors
To counter the drift issues of relative sensors, arculee uses absolute sensors such as laser scanners (LiDAR) to obtain a precise, external reference of its position in the environment. These scanners were originally part of the robot’s safety system, ensuring safe operation around humans. But with free navigation, they now also serve the additional function of enabling accurate localisation.
The laser scanners provide an absolute reference by recognising features in the environment, which improves navigation accuracy and allows the robot to maintain reliable position estimates without physical markers.
Laser (LiDAR) scanner, installed initially for ensuring safety, also assists in accurate localisation
2. Localisation
Once the sensors have gathered data, the next step is to determine the robot's exact location within the environment. This process is known as localisation, and it begins with mapping through a technique known as Simultaneous Localisation and Mapping (SLAM).
SLAM: Building a Map to Get Around
SLAM creates a contour map or grid-based map of the robot’s environment. This map resembles a table-like structure where each cell represents a small portion of the space. Each cell is marked as either occupied (e.g., by a wall or pillar, etc) or free (when the laser detects nothing).
During operation, the robot continuously generates a "snapshot" of its surroundings using the laser scanner. It then matches this snapshot with the pre-generated SLAM map using nonlinear optimisation techniques. This matching process estimates where the robot is most likely positioned in the map.
By combining this absolute position estimate with the data from relative sensors (IMU and wheel speed), the arculee can accurately determine its current location and orientation within the warehouse. Dennis explains:
"This fusion of relative and absolute sensing, anchored by the SLAM map, ensures robust localisation even over long distances without relying on QR codes or physical landmarks."
SLAM map, along with the relative and absolute sensing, ensures robust localisation in warehouses
How Do arculees Solve the Accuracy Challenge
High-accuracy scenarios, such as entering a pallet handover station or picking up a table, are crucial for arculee’s performance. Such use cases pose a unique technical challenge. To handle these, arculee switches to a specialised mode of localisation that no longer references the global map, but instead focuses solely on the object in front of it.
“Think of it like parking a car: once you see the parking space, your only goal is to drive into it precisely, everything else in the environment becomes irrelevant,” explains Dennis, “similarly, arculee approaches the target, detects it using a robust template-matching algorithm, and then begins precise positioning relative to that object.”
The arculees use a targeted, fine-grained contour map for their accurate and reliable positioning
At this point, arculee uses a high-resolution contour map with accuracy in the millimetre range to match incoming laser scans and guide movement. This targeted, fine-grained scan matching allows the robot to move in and out of stations reliably and accurately.
Whether it’s an in-house-designed station or a customer-provided object, arculee can quickly model the geometry and begin operating with precision, without any need for QR code markers. This flexibility makes it highly adaptable in diverse warehouse environments.
Fast + Reliable = Efficient
One noteworthy feature of arculee’s navigation system is its ability to provide fast and accurate absolute updates of the robot’s position, all while running on a small, integrated, low-power compute platform.
Dennis highlights that this efficiency comes from a smart architecture that balances cutting-edge precision with lightweight performance:
"We achieve this (efficiency) because while we use state-of-the-art non-linear optimisation techniques to find the best match of the laser scan with the map, on the backend, we rely on a lightweight state estimation that is very fast compared to some of the frameworks that are popular within the industry."
Dennis, in discussion with Eugenio
Making a Difference
Free navigation is more than a clever trick; it’s a crucial step in how AMRs like arculees move, adapt, and scale. By using what’s already present, the robot’s onboard sensors and the natural contours of the environment, arculus eliminates the need for costly infrastructure, while enhancing precision and safety.
The result? Flexible automation that stays accurate without constant maintenance.
As Dennis puts it,
"We’re using the tools we already have on the robot in smarter ways. That’s what makes the difference."
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